Best estimates for the UK public sector suggest that between £31bn and £53bn is being lost from the public purse to fraud and error each year.
This is a challenge that requires a constant effort to tackle, and while fraud is an age-old crime, with the rise of the digital age, criminals are finding new and imaginative ways to deceive our public services and it is often difficult for traditional point fraud solutions to handle.
However, just as how fraud has been committed has evolved, so too has the technology available to detect and catch fraudsters. Government departments should embrace it.
As the mountain of records and data that UK public sector organisations have on file continues to grow across disparate systems, it becomes increasingly difficult to understand and gain value from it.
But the fact that the data is in there in the first place is a good start. The missing piece is the ability to analyse it, see it in context and actually gain insight from it. Which is how governments can start to use what they know to improve what they do to counter fraud.
AI, Machine Learning and Big Data technologies have reached a mature and affordable enough state to tackle fraud in a systematic and robust way at scale.
By developing and launching state-of-the-art algorithms, AI aims to detect identity theft, cloning and entity data anomaly techniques, which have been commonly used by organised criminal gangs committing mass-scale benefit fraud.
This type of fraud is an area where AI can prove especially useful, as it can identify possible issues far quicker than human investigators across huge amounts of data.
While this of course does not remove the need for human oversight, there should always be a “human infusion”, it can greatly increase the efficiency of investigations, and free up resources to tackle the major cases. It also enhances the toolset available to investigators by providing another means of detecting fraud, other than tips from the public or the traditional point solutions.
The Public Sector would need to manage the possible risk of embedding and industrialising unconscious or historic biases in complex data sets.
For example the 2018 report on Algorithms in Decision Making, by the Science and Technology Committee, called for the “right to explanation”, so that citizens can demand to know how machine-learning programmes have made decisions that affect them. The committee also suggested the creation of a new ministerial position to oversee the government’s use of algorithms, with the aim of facilitating a more joined-up approach across Whitehall.
However, AI technology has been flagged as the tool of the future in the fight against fraud. The Association of Certified Fraud Examiners (ACFE) states that the use of AI for fraud detection will triple by 2021.
Many private sector organisations have been investing in AI and machine learning to take on fraud undoubtedly, with large data sets. Government is a place where AI can make a significant impact, and I expect it will likely become an integral part of how the government combats fraud in the future, whilst maintaining a wider duty to ensure that transparency and public trust are at the heart of the public sector’s use of that technology.
Experian are sponsoring ‘The International Counter Fraud Data Analytics Conference 2020’ in March. Along with other public and private sector partners, will be sharing our experiences of using data and analytics to fight fraud and error in Government. We’re looking forward to being part of this discussion and helping drive the fight against fraud in the future.
Want to be a part of the discussion? Register here